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Accuracy and time efficiency are two essential requirements for theself-localization of autonomous vehicles. While the observation rangeconsidered for simultaneous localization and mapping (SLAM) has a significanteffect on both accuracy and computation time, its effect is not wellinvestigated in the literature. In this paper, we will answer the question: Howfar should a driverless car observe during self-localization? We introduce aframework to dynamically define the observation range for localization to meetthe accuracy requirement for autonomous driving, while keeping the computationtime low. To model the effect of scanning range on the localization accuracyfor every point on the map, several map factors were employed. The capabilityof the proposed framework was verified using field data, demonstrating that itis able to improve the average matching time from 142.2 ms to 39.3 ms whilekeeping the localization accuracy around 8.1 cm.

How far should self-driving cars see? Effect of observation range on vehicle self-localization